Cognitive Architectures for Physical Agents

Icarus is a computational theory of the cognitive architecture that
incorporates ideas from multiple traditions, including work on
production systems, hierarchical task networks, and logic programming.
The framework relies on five assumptions that distinguish it from
alternative candidates:

Cognition is grounded in perception and action;

Categories and skills are distinct types of cognitive structure;

Short-term elements are instances of long-term structures;

Long-term knowledge is organized in a hierarchical manner; and

Inference has primacy over execution, which has primacy over
problem solving.
Our papers explain these assumptions and particular abilities in
more detail. We have used Icarus to develop a number of synthetic
characters for simulated environments, as well as for traditional
tasks from the AI and cognitive science literature. Current research
includes incorporating mechanisms for forward-chaining problem solving,
counterfactual reasoning, model-based learning from delayed reward,
generating episodic traces, and learning from other agents' behaviors.

This research has been funded by DARPA IPTO, the Office of Naval
Research, and the National Science Foundation. Support for earlier
work came from the Air Force Office of Scientific Research, NASA Ames
Research Center, and DaimlerChrysler Research and Technology.